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Sensitivity analysis for importance assessment.

Andrea Saltelli1

  • 1Institute for the Protection and Security of the Citizen (IPSC), The European Commission, Joint Research Centre TP ISPRA(VA) Italy. andrea.saltelli@jrc.it

Risk Analysis : an Official Publication of the Society for Risk Analysis
|June 29, 2002
PubMed
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Quantitative sensitivity analysis can enhance model-based analysis. This review outlines the necessary features and methods for its expanded application in scientific research.

Area of Science:

  • Computational Science
  • Mathematical Modeling
  • Statistical Analysis

Background:

  • Model-based analysis is crucial in various scientific disciplines.
  • Quantitative sensitivity analysis (QSA) is a key tool for understanding model behavior.
  • Current applications of QSA may not fully leverage its potential.

Purpose of the Study:

  • To explore an extended role for QSA in model-based analysis.
  • To define the essential features of QSA for advanced applications.
  • To identify suitable QSA methods and provide practical examples.

Main Methods:

  • Review of existing literature and examples supporting extended QSA.
  • Identification and description of necessary QSA features.
  • Presentation of QSA methods meeting these requirements.

Related Experiment Videos

  • Illustrative example of QSA application.

    • Main Results:

    • Examples demonstrating the value of QSA beyond basic applications.
    • Defined criteria for effective QSA in complex models.
    • Overview of advanced QSA methodologies.
    • A practical case study showcasing QSA implementation.

    Conclusions:

    • QSA offers significant potential for enhancing model-based analysis.
    • Specific features and methods are required for this extended role.
    • Further research can advance the application of QSA in science.